code: def _tile_chunks(cls, op, xa, xb, w, v, vi):
      out_tensor = op.outputs[0]
      acs, bcs = xa.chunk_shape[0], xb.chunk_shape[0]
  
      out_chunks = []
      for idx in itertools.product(range(acs), range(bcs)):
          ixa, ixb = idx
          chunk_op = op.copy().reset_key()
  
          chunk_inputs = []
          xa_chunk = xa.cix[ixa, 0]
          xb_chunk = xb.cix[ixb, 0]
          chunk_inputs.extend([xa_chunk, xb_chunk])
          if w is not None:
              w_chunk = chunk_op._w = w.chunks[0]
              chunk_inputs.append(w_chunk)
          if v is not None:
              v_chunk = chunk_op._v = v.chunks[0]
              chunk_inputs.append(v_chunk)
          if vi is not None:
              vi_chunk = chunk_op._vi = vi.chunks[0]
              chunk_inputs.append(vi_chunk)
          chunk = chunk_op.new_chunk(
              chunk_inputs,
              shape=(xa_chunk.shape[0], xb_chunk.shape[0]),
              order=out_tensor.order,
              index=idx,
          )
          out_chunks.append(chunk)
  
      new_op = op.copy()
      return new_op.new_tensors(
          op.inputs,
          shape=out_tensor.shape,
          order=out_tensor.order,
          chunks=out_chunks,
          nsplits=(xa.nsplits[0], xb.nsplits[0]),
      )
  
imports: import itertools
  from typing import Tuple
  import numpy
  from ....None import opcodes
  from ....core import recursive_tile
  from ....serialization.serializables import KeyField, AnyField, Float16Field
  from ....utils import has_unknown_shape, require_module, ensure_own_data
  from ...operands import TensorOperand, TensorOperandMixin
  from ...core import TensorOrder
  from ...datasource import tensor
  from ...array_utils import as_same_device, cp, device
label_desc: Use image node_id 12 for calling the TensorCdist obj's underlying member method code with example usage: obj._tile_chunks(cls, op, xa, xb, w, v, vi) and returns: new_op